1. Field of the Invention
This invention relates in general to data read channels, and more particularly to an apparatus for providing data dependent detection in a data read channel.
2. Description of Related Art
Recently developed data storage devices, such as magnetic disk drive devices (i.e., hard disk drives), have increased storage capacity and increased data access speed. With these advantages, magnetic disk drive devices have become widely used as auxiliary memory devices for computer systems. More generally, developments in pulse communications related to these improvements in disk drive technology have recently provided increased speed and reliability in a wide range of pulse communications systems. The present invention will be described in detail in the context of magnetic disk drive devices, but persons skilled in the pulse communications arts will readily apprehend that this invention provides an improved method for data pulse detection in a wide variety of pulse communication contexts.
The primary features of a magnetic disk drive device that affect storage capacity and access speed are the head, the recording medium, the servo mechanism, the signal processing technique used in the read/write channel, and the like. Among these, signal processing techniques utilizing PRML (Partial Response Maximum Likelihood) detection have greatly contributed to the increased storage capacities and high access speeds seen in modern magnetic disk drive devices.
A read channel circuit in a generic read/write channel circuit of a magnetic disk drive device includes components for initial processing of the analog read signal generated by the read/write head of the device. This processing provides automatic gain control (AGC) amplification, filtering, and equalization, as well as analog-to-digital conversion.
As areal densities increase, inter-symbol interference (ISI), transition-dependent noise and non-linear distortions at high densities and bandwidth limitations at high data rates lead to performance degradation. For example, the level of inter-symbol interference between neighboring recorded bits in magnetic recording channels increases with recording density. Further, there are many sources of noise that contribute to a loss in error rate including data dependent noise sources such as transition noise.
To recover data from a noise contaminated read back signal, read channels receive an analog signal from the preamplifier and send detected data in digital form to the disk drive controller. The read-write channels that are currently most commonly used are based on the partial response approach. In this approach, the channel impulse and a Viterbi detector are used for detecting the data pulses in the digitized read signal and recovering the bits. Advanced replay equalizations have been adopted in the magnetic recording technology to shape the channel pulse response to some specified target shape, which has a shorter duration (higher bandwidth) and this is called partial-response signaling or equalization. A Viterbi detector that is matched to the target shape normally follows the partial response equalizer. Maintaining precisely the desired partial response shape through adaptive equalizations at the channel output permits the Viterbi detector to be efficiently realized and hence improving the bit detection quality. The overall task of the detector is to recover the encoded data that was originally recorded on the magnetic medium.
In this context, such a detector receives an equalized digital read signal and generates from it an encoded data signal, which is then decoded to produce the final read data signal. The various components in such a read/write channel circuit introduce into the design and manufacturing process various parameters whose values affect the data storage density and the access speed of the device.
At the heart of the Viterbi decoding algorithm is the trellis, which is an extension of the encoder state machine that shows the passage of time. A section of the trellis shows the possible state transitions and output codewords for one period of the encoder. Every branch between two states represents a possible state change in the encoder. The Viterbi procedure determines the best path (most likely sequence of symbols from a finite alphabet) ending in each state j, where state j represents the memory in the channel, by comparing the samples in the sample sequence y0, y1, . . . yn to the expected sequence of read back samples associated with all possible paths that can end in state j at time n.
The “best path” is determined typically by comparing the Euclidean distance between the actual and expected read back sample sequences. This Euclidean distance is often referred to as the state metric (also called the path metric). The best path ending in state j is often defined to be the expected read back sample sequence with the smallest state metric. As known in the art, the state metric can be defined in terms other than the Euclidean distance.
The Euclidean branch metrics may be adjusted based on data dependent noise or its signal dependent structure. However, to adjust the Euclidean branch metrics, separate functions for various states are required. The conventional Viterbi detector operating on an arbitrary generalized partial-response target with L coefficients requires 2L−1 states with 2L branch metrics. For example, for a target having a length of 5, a 16 state Viterbi is needed.
In a real system there are many sources of noise contributing to a loss in error rate. As described above, the primary function of the disk drive read channel is to reliably recover data from a noise contaminated read back signal. A detection algorithm exploiting the structure of data dependent noise sources is needed to improve the overall error rate. In U.S. Pat. No. 6,102,839, issued Mar. 13, 2001 to Kavcic et al., a method and apparatus for determining branch metric values for branches of a trellis for a Viterbi-like detector was described. According to Kavcic et al., a noise predictive filter and scale was used in every branch of the detector trellis. However, a drawback of this approach is the large complexity associated with a hardware implementation.
It can be seen then that there is a need for an apparatus for providing data dependent detection in a data read channel.